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This paper presents a new robotic navigation aid, called Co-Robotic Cane (CRC). The CRC uses a 3D camera for both pose estimation and object recognition in an unknown indoor environment. The 6-DOF pose estimation method determines the CRC's pose change by an egomotion estimation method and the iterative closest point algorithm and reduces the pose integration error by a pose graph optimization algorithm. The pose estimation method does not require any prior knowledge of the environment. The object recognition method detects indoor structures such as stairways, doorways, etc. and objects such as tables, computer monitors, etc. by a Gaussian Mixture Model based pattern recognition method. Some structures/objects (e.g., stairways) can be used as navigational waypoints and the others for obstacle avoidance. The CRC can be used in either robot cane (active) mode or white cane (passive) mode. In the active mode it guides the user by steering itself into the desired direction of travel, while in the passive mode it functions as a computer-vision-enhanced white cane. The CRC is a co-robot. It can detect human intent and use the intent to select a suitable mode automatically.
Ye et al. (Fri,) studied this question.